To be published in 2012 in Proceedings of the 5th International Workshop on Semantic Sensor Networks
Ruben Verborgh, Vincent Haerinck, Thomas Steiner, Davy Van Deursen, Sofie Van Hoecke, Jos De Roo, Rik Van de Walle, and Joaquim Gabarró Vallés
“Web APIs are becoming an increasingly popular alternative to the more heavy-weight Web services. Recently, they also have been used in the context of sensor networks. However, making different Web APIs (and thus sensors) cooperate often requires a significant amount of manual configuration. Ideally, we want Web APIs to behave like Linked Data, where data from different sources can be combined in a straightforward way. Therefore, in this paper, we show how Web APIs, semantically described by the light-weight format RESTdesc, can be composed automatically based on their functionality. Moreover, the composition process does not require specific tools, as compositions are created by generic Semantic Web reasoners as part of a proof. We then indicate how the composition in this proof can be executed. We describe our architecture and implementation, and validate that proof-based composition is a feasible strategy on a Web scale. Our measurements indicate that current reasoners can integrate compositions of more than 200 Web APIs in under one second. This makes proof-based composition a practical choice for today’s Web APIs.”
International Journal of Geographical Information Science, Volume 26, Issue 4, 2012
Francisco J. Lopez-Pellicer, Javier Lacasta, Aneta Florczyk, Javier Nogueras-Iso & F. Javier Zarazaga-Soria
“Jurisdictional domains are generally accepted political divisions of the earth surface that cover specific territorial and functional scopes over time. They are frequently used in information retrieval (IR) to classify and locate resources by means of their geographical location. However, the changes they suffer over time reduce their applicability in historical collections. In this context, and with the objective of improving the use of jurisdictional domains, this article proposes an ontology schema that combines in a single model the administrative structure, the spatial components, and the temporal evolution of jurisdictional domains. This ontology schema has been used to create the Spanish jurisdictional model. Additionally, as an example of its applicability in the IR context, the Spanish model has been used as part of a location-based query component for the Spanish Official State Gazette.”
Computers & Geosciences
, Volume 45, August 2012, Pages 199–211
Dieu Tien Bui, Biswajeet Pradhan, Owe Lofman, Inge Revhaug, and Oystein B. Dick
“The objective of this study is to investigate a potential application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) and the Geographic Information System (GIS) as a relatively new approach for landslide susceptibility mapping in the Hoa Binh province of Vietnam. Firstly, a landslide inventory map with a total of 118 landslide locations was constructed from various sources. Then the landslide inventory was randomly split into a testing dataset 70% (82 landslide locations) for training the models and the remaining 30% (36 landslides locations) was used for validation purpose. Ten landslide conditioning factors such as slope, aspect, curvature, lithology, land use, soil type, rainfall, distance to roads, distance to rivers, and distance to faults were considered in the analysis. The hybrid learning algorithm and six different membership functions (Gaussmf, Gauss2mf, Gbellmf, Sigmf, Dsigmf, Psigmf) were applied to generate the landslide susceptibility maps.
Landslide inventory of the study area.
“The validation dataset, which was not considered in the ANFIS modeling process, was used to validate the landslide susceptibility maps using the prediction rate method. The validation results showed that the area under the curve (AUC) for six ANFIS models vary from 0.739 to 0.848. It indicates that the prediction capability depends on the membership functions used in the ANFIS. The models with Sigmf (0.848) and Gaussmf (0.825) have shown the highest prediction capability. The results of this study show that landslide susceptibility mapping in the Hoa Binh province of Vietnam using the ANFIS approach is viable. As far as the performance of the ANFIS approach is concerned, the results appeared to be quite satisfactory, the zones determined on the map being zones of relative susceptibility.”
Computers & Geosciences, Volume 45, August 2012, Pages 98–108
Kristin Stock, Tim Stojanovic, Femke Reitsma, Yang Ou, Mohamed Bishr, Jens Ortmann, and Anne Robertson
“A geospatial knowledge infrastructure consists of a set of interoperable components, including software, information, hardware, procedures and standards, that work together to support advanced discovery and creation of geoscientific resources, including publications, data sets and web services. The focus of the work presented is the development of such an infrastructure for resource discovery. Advanced resource discovery is intended to support scientists in finding resources that meet their needs, and focuses on representing the semantic details of the scientific resources, including the detailed aspects of the science that led to the resource being created.
“This paper describes an information model for a geospatial knowledge infrastructure that uses ontologies to represent these semantic details, including knowledge about domain concepts, the scientific elements of the resource (analysis methods, theories and scientific processes) and web services. This semantic information can be used to enable more intelligent search over scientific resources, and to support new ways to infer and visualise scientific knowledge.
The COMPASS user interface.
“The work describes the requirements for semantic support of a knowledge infrastructure, and analyses the different options for information storage based on the twin goals of semantic richness and syntactic interoperability to allow communication between different infrastructures. Such interoperability is achieved by the use of open standards, and the architecture of the knowledge infrastructure adopts such standards, particularly from the geospatial community. The paper then describes an information model that uses a range of different types of ontologies, explaining those ontologies and their content. The information model was successfully implemented in a working geospatial knowledge infrastructure, but the evaluation identified some issues in creating the ontologies.”
GeoInformatica, Published Online 27 October 2011
Xiang Zhang, Tinghua Ai, Jantien Stoter, Menno-Jan Kraak, and Martien Molenaar
“Building patterns are important features that should be preserved in the map generalization process. However, the patterns are not explicitly accessible to automated systems. This paper proposes a framework and several algorithms that automatically recognize building patterns from topographic data, with a focus on collinear and curvilinear alignments. For both patterns two algorithms are developed, which are able to recognize alignment-of-center and alignment-of-side patterns. The presented approach integrates aspects of computational geometry, graph-theoretic concepts and theories of visual perception. Although the individual algorithms for collinear and curvilinear patterns show great potential for each type of the patterns, the recognized patterns are neither complete nor of enough good quality. We therefore advocate the use of a multi-algorithm paradigm, where a mechanism is proposed to combine results from different algorithms to improve the recognition quality. The potential of our method is demonstrated by an application of the framework to several real topographic datasets. The quality of the recognition results are validated in an expert survey.”
GeoInformatica, Published Online 06 March 2012
Jonathon K. Parker and Joni A. Downs
“Geometric footprints, which delineate the region occupied by a spatial point pattern, serve a variety of functions in GIScience. This research explores the use of two density-based clustering algorithms for footprint generation. First, the Density-Based Spatial Clustering with Noise (DBSCAN) algorithm is used to classify points as core points, non-core points, or statistical noise; then a footprint is created from the core and non-core points in each cluster using convex hulls. Second, a Fuzzy-Neighborhood (FN)-DBSCAN algorithm, which incorporates fuzzy set theory, is used to assign points to clusters based on membership values. Then, two methods are presented for delineating footprints with FN-DBSCAN: (1) hull-based techniques and (2) contouring methods based on interpolated membership values. The latter approach offers increased flexibility for footprint generation, as it provides a continuous surface of membership values from which precise contours can be delineated. Then, a heuristic parameter selection method is described for FN-DBSCAN, and the approach is demonstrated in the context of wildlife home range estimation, where the goal is to a generate footprint of an animal’s movements from tracking data. Additionally, FN-DBSCAN is applied to produce crime footprints for a county in Florida. The results are used to guide a discussion of the relative merits of the new techniques. In summary, the fuzzy clustering approach offers a novel method of footprint generation that can be applied to characterize a variety of point patterns in GIScience.”
Sensors 2012, 12(5), 6307-6330, published online 11 May 2012
Álvaro Sigüenza, David Díaz-Pardo, Jesús Bernat, Vasile Vancea, José Luis Blanco, David Conejero, and Luis Hernández Gómez
“Current “Internet of Things” concepts point to a future where connected objects gather meaningful information about their environment and share it with other objects and people. In particular, objects embedding Human Machine Interaction (HMI), such as mobile devices and, increasingly, connected vehicles, home appliances, urban interactive infrastructures, etc., may not only be conceived as sources of sensor information, but, through interaction with their users, they can also produce highly valuable context-aware human-generated observations. We believe that the great promise offered by combining and sharing all of the different sources of information available can be realized through the integration of HMI and Semantic Sensor Web technologies. This paper presents a technological framework that harmonizes two of the most influential HMI and Sensor Web initiatives: the W3C’s Multimodal Architecture and Interfaces (MMI) and the Open Geospatial Consortium (OGC) Sensor Web Enablement (SWE) with its semantic extension, respectively.
Experimental setup for publishing driver-generated observations in the Semantic Sensor Web.
“Although the proposed framework is general enough to be applied in a variety of connected objects integrating HMI, a particular development is presented for a connected car scenario where drivers’ observations about the traffic or their environment are shared across the Semantic Sensor Web. For implementation and evaluation purposes an on-board OSGi (Open Services Gateway Initiative) architecture was built, integrating several available HMI, Sensor Web and Semantic Web technologies. A technical performance test and a conceptual validation of the scenario with potential users are reported, with results suggesting the approach is sound.”
The popular “Essays on Geography and GIS” e-book series brings together a broad range of articles written by academicians and scientists dealing with trends in geography, geospatial matters, and GIS. More than 100,000 copies of the first three volumes have been downloaded over the last three and a half years. Today, Esri released Volume 4 in this series, which features the following articles:
- Through the Macroscope: Geography’s View of the World
- A Role for Old-Fashioned Geographia in Education
- Zen and the Art of GIS Communication
- Ecosystem Services—Learning to Leverage Natural Capital
- Looking Forward: Five Thoughts on the Future of GIS
- The Future Looks Bright for Spatial Thinkers
- Scaling Up Classroom Maps
- Managing Our Man-Made Ecosystems
- GIS and Geography: Interactions with the Humanities
- The Challenge of Defining Geo-Literacy
- Let’s Exchange Competition for Cooperation
- A National GIS Infrastructure for Health Research
- The Intersection of GIS and Gaming
- Understanding Our World
- From Maps to GeoDesign
- Making Sense of Our Sensored Planet
- Hand in Hand—Spatial Information for Latin America
- Delivering GIS in a Period of Unsustainable Growth
Read Vol. 4 [PDF]
The first three volumes are also still available:
GSDI World Conference (GSDI 13), 14-17 May 2012, Québec City, Canada
Stéphane Roche, Nashid Nabian, Kristian Kloeckl, and Carlo Ratti
“In our contemporary societal context, reconfigured by wide spread impact of Geolocalization and wikification on urban population’s everyday work and life, two related concepts, “spatially enabled society” and “smart city”, have emerged from two different but related fields: the Global Spatial Data Infrastructure community drives the former while practitioners and researchers in urban planning, urban studies and urban design are more concerned with the latter. We believe that technology enhanced, ICT‐driven solutions that spatially enable the members of urban populations, contribute to smart operation of cities, and we suggest that a dialogue between the communities that foster these two notions needs to be established. We seek to provide an ontology of categorically different, but still related, spatial enablement scenarios along with speculations on how each category can enhance the Smart City agenda by empowering the urban population, using recent projects by the MIT SENSEable City Lab to illustrate our points.”
GeoInformatica, Published Online 14 March 2012
Wei-Shinn Ku, Ling Hu, Cyrus Shahabi, and Haixun Wang
“With the trend of cloud computing, outsourcing databases to third party service providers is becoming a common practice for data owners to decrease the cost of managing and maintaining databases in-house. In conjunction, due to the popularity of location-based-services (LBS), the need for spatial data (e.g., gazetteers, vector data) is increasing dramatically. Consequently, there is a noticeably new tendency of outsourcing spatial datasets by data collectors. Two main challenges with outsourcing datasets are to keep the data private (from the data provider) and to ensure the integrity of the query result (for the clients). Unfortunately, most of the techniques proposed for privacy and integrity do not extend to spatial data in a straightforward manner. Hence, recent studies proposed various techniques to support either privacy or integrity (but not both) on spatial datasets. In this paper, for the first time, we propose a technique that can ensure both privacy and integrity for outsourced spatial data. In particular, we first use a one-way spatial transformation method based on Hilbert curves, which encrypts the spatial data before outsourcing and, hence, ensures its privacy. Next, by probabilistically replicating a portion of the data and encrypting it with a different encryption key, we devise a technique for the client to audit the trustworthiness of the query results. We show the applicability of our approach for both k-nearest-neighbor queries and spatial range queries, which are the building blocks of any LBS application. We also design solutions to guarantee the freshness of outsourced spatial databases. Finally, we evaluate the validity and performance of our algorithms with security analyses and extensive simulations. ”